Text Generation
Transformers
Safetensors
English
glm_moe_dsa
code
coding
software-engineering
Mixture of Experts
fp8
glm
glm-5.2
vllm
conversational
Instructions to use jelegend/GLM-5.2-FP8-Finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jelegend/GLM-5.2-FP8-Finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="jelegend/GLM-5.2-FP8-Finetuned") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("jelegend/GLM-5.2-FP8-Finetuned") model = AutoModelForCausalLM.from_pretrained("jelegend/GLM-5.2-FP8-Finetuned") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use jelegend/GLM-5.2-FP8-Finetuned with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "jelegend/GLM-5.2-FP8-Finetuned" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jelegend/GLM-5.2-FP8-Finetuned", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/jelegend/GLM-5.2-FP8-Finetuned
- SGLang
How to use jelegend/GLM-5.2-FP8-Finetuned with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "jelegend/GLM-5.2-FP8-Finetuned" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jelegend/GLM-5.2-FP8-Finetuned", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "jelegend/GLM-5.2-FP8-Finetuned" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jelegend/GLM-5.2-FP8-Finetuned", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use jelegend/GLM-5.2-FP8-Finetuned with Docker Model Runner:
docker model run hf.co/jelegend/GLM-5.2-FP8-Finetuned
Upload chat_template.jinja
Browse files- chat_template.jinja +119 -0
chat_template.jinja
ADDED
|
@@ -0,0 +1,119 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
[gMASK]<sop>
|
| 2 |
+
{%- set effective_reasoning_effort = 'high' if reasoning_effort is defined and reasoning_effort == 'high' else 'max' -%}
|
| 3 |
+
{%- if (enable_thinking is not defined or enable_thinking) and effective_reasoning_effort is not none -%}<|system|>Reasoning Effort: {{ effective_reasoning_effort | capitalize }}{%- endif -%}
|
| 4 |
+
{%- if tools -%}
|
| 5 |
+
{%- macro tool_to_json(tool) -%}
|
| 6 |
+
{%- set ns_tool = namespace(first=true) -%}
|
| 7 |
+
{{ '{' -}}
|
| 8 |
+
{%- for k, v in tool.items() -%}
|
| 9 |
+
{%- if k != 'defer_loading' and k != 'strict' -%}
|
| 10 |
+
{%- if not ns_tool.first -%}{{- ', ' -}}{%- endif -%}
|
| 11 |
+
{%- set ns_tool.first = false -%}
|
| 12 |
+
"{{ k }}": {{ v | tojson(ensure_ascii=False) }}
|
| 13 |
+
{%- endif -%}
|
| 14 |
+
{%- endfor -%}
|
| 15 |
+
{{- '}' -}}
|
| 16 |
+
{%- endmacro -%}
|
| 17 |
+
<|system|>
|
| 18 |
+
# Tools
|
| 19 |
+
|
| 20 |
+
You may call one or more functions to assist with the user query.
|
| 21 |
+
|
| 22 |
+
You are provided with function signatures within <tools></tools> XML tags:
|
| 23 |
+
<tools>
|
| 24 |
+
{% for tool in tools %}
|
| 25 |
+
{%- if 'function' in tool -%}
|
| 26 |
+
{%- set tool = tool['function'] -%}
|
| 27 |
+
{%- endif -%}
|
| 28 |
+
{% if tool.defer_loading is not defined or not tool.defer_loading %}
|
| 29 |
+
{{ tool_to_json(tool) }}
|
| 30 |
+
{% endif %}
|
| 31 |
+
{% endfor %}
|
| 32 |
+
</tools>
|
| 33 |
+
|
| 34 |
+
For each function call, output the function name and arguments within the following XML format:
|
| 35 |
+
<tool_call>{function-name}<arg_key>{arg-key-1}</arg_key><arg_value>{arg-value-1}</arg_value><arg_key>{arg-key-2}</arg_key><arg_value>{arg-value-2}</arg_value>...</tool_call>{%- endif -%}
|
| 36 |
+
{%- macro visible_text(content) -%}
|
| 37 |
+
{%- if content is string -%}
|
| 38 |
+
{{- content }}
|
| 39 |
+
{%- elif content is iterable and content is not mapping -%}
|
| 40 |
+
{%- for item in content -%}
|
| 41 |
+
{%- if item is mapping and item.type == 'text' -%}
|
| 42 |
+
{{- item.text }}
|
| 43 |
+
{%- elif item is string -%}
|
| 44 |
+
{{- item }}
|
| 45 |
+
{%- elif item is mapping and item.type in ['image', 'image_url', 'video', 'video_url', 'audio', 'audio_url', 'input_audio'] -%}
|
| 46 |
+
{%- set media_type = item.type | replace('_url', '') | replace('input_', '') -%}
|
| 47 |
+
{{- "<reminder>You are unable to process this " ~ media_type ~ " because you don't have multi-modal input ability. Try different methods.</reminder>" }}
|
| 48 |
+
{%- endif -%}
|
| 49 |
+
{%- endfor -%}
|
| 50 |
+
{%- else -%}
|
| 51 |
+
{{- content }}
|
| 52 |
+
{%- endif -%}
|
| 53 |
+
{%- endmacro -%}
|
| 54 |
+
{%- set ns = namespace(last_user_index=-1) -%}
|
| 55 |
+
{%- for m in messages %}
|
| 56 |
+
{%- if m.role == 'user' %}
|
| 57 |
+
{%- set ns.last_user_index = loop.index0 -%}
|
| 58 |
+
{%- endif %}
|
| 59 |
+
{%- endfor %}
|
| 60 |
+
{%- for m in messages -%}
|
| 61 |
+
{%- if m.role == 'user' -%}<|user|>{{ visible_text(m.content) }}
|
| 62 |
+
{%- elif m.role == 'assistant' -%}
|
| 63 |
+
<|assistant|>
|
| 64 |
+
{%- set content = visible_text(m.content) %}
|
| 65 |
+
{%- if m.reasoning_content is string %}
|
| 66 |
+
{%- set reasoning_content = m.reasoning_content %}
|
| 67 |
+
{%- elif '</think>' in content %}
|
| 68 |
+
{%- set reasoning_content = content.split('</think>')[0].split('<think>')[-1] %}
|
| 69 |
+
{%- set content = content.split('</think>')[-1] %}
|
| 70 |
+
{%- endif %}
|
| 71 |
+
{%- if ((clear_thinking is defined and not clear_thinking) or loop.index0 > ns.last_user_index) and reasoning_content is defined -%}
|
| 72 |
+
{{ '<think>' + reasoning_content + '</think>'}}
|
| 73 |
+
{%- else -%}
|
| 74 |
+
{{ '<think></think>' }}
|
| 75 |
+
{%- endif -%}
|
| 76 |
+
{%- if content.strip() -%}
|
| 77 |
+
{{ content.strip() }}
|
| 78 |
+
{%- endif -%}
|
| 79 |
+
{% if m.tool_calls %}
|
| 80 |
+
{% for tc in m.tool_calls %}
|
| 81 |
+
{%- if tc.function %}
|
| 82 |
+
{%- set tc = tc.function %}
|
| 83 |
+
{%- endif %}
|
| 84 |
+
{{- '<tool_call>' + tc.name -}}
|
| 85 |
+
{% set _args = tc.arguments %}{% for k, v in _args.items() %}<arg_key>{{ k }}</arg_key><arg_value>{{ v | tojson(ensure_ascii=False) if v is not string else v }}</arg_value>{% endfor %}</tool_call>{% endfor %}
|
| 86 |
+
{% endif %}
|
| 87 |
+
{%- elif m.role == 'tool' -%}
|
| 88 |
+
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
|
| 89 |
+
{{- '<|observation|>' -}}
|
| 90 |
+
{%- endif %}
|
| 91 |
+
{%- if m.content is string -%}
|
| 92 |
+
{{- '<tool_response>' + m.content + '</tool_response>' -}}
|
| 93 |
+
{%- elif m.content is iterable and m.content is not mapping and m.content and m.content.0.type == "tool_reference" -%}
|
| 94 |
+
{{- '<tool_response><tools>\n' -}}
|
| 95 |
+
{% for tr in m.content %}
|
| 96 |
+
{%- for tool in tools -%}
|
| 97 |
+
{%- if 'function' in tool -%}
|
| 98 |
+
{%- set tool = tool['function'] -%}
|
| 99 |
+
{%- endif -%}
|
| 100 |
+
{%- if tool.name == tr.name -%}
|
| 101 |
+
{{- tool_to_json(tool) + '\n' -}}
|
| 102 |
+
{%- endif -%}
|
| 103 |
+
{%- endfor -%}
|
| 104 |
+
{%- endfor -%}
|
| 105 |
+
{{- '</tools></tool_response>' -}}
|
| 106 |
+
{%- elif m.content is iterable and m.content is not mapping and m.content and m.content.0 is mapping and m.content.0.output is defined -%}
|
| 107 |
+
{%- for tr in m.content -%}
|
| 108 |
+
{{- '<tool_response>' + tr.output + '</tool_response>' -}}
|
| 109 |
+
{%- endfor -%}
|
| 110 |
+
{%- else -%}
|
| 111 |
+
{{- '<tool_response>' + visible_text(m.content) + '</tool_response>' -}}
|
| 112 |
+
{% endif -%}
|
| 113 |
+
{%- elif m.role == 'system' -%}
|
| 114 |
+
<|system|>{{ visible_text(m.content) }}
|
| 115 |
+
{%- endif -%}
|
| 116 |
+
{%- endfor -%}
|
| 117 |
+
{%- if add_generation_prompt -%}
|
| 118 |
+
<|assistant|>{{- '<think></think>' if (enable_thinking is defined and not enable_thinking) else '<think>' -}}
|
| 119 |
+
{%- endif -%}
|